摘要
针对传统的灰色预测模型对建筑物沉降预测精度不高、拟合数据较差的问题,在传统的GM（1,1）模型基础上提出了分数阶建模的思想,采用粒子群优化算法求解最优分数阶次,建立基于粒子群优化的分数阶PFGM（1,1）模型.实例计算表明,分数阶FGM（1,1）模型可以提高建筑物沉降的预测精度,通过粒子群优化算法选取最优阶次可以进一步提高预测精度和误差检验等级.由此可见,基于粒子群优化的分数阶PFGM（1,1）模型对建筑物的沉降控制有着重要的指导作用.
The idea of fractional order modeling was put forward in this paper based on the traditional GM （1,1） model as to the problems of low precision of building settlement prediction and poor fitting data, which the traditional gray forecasting model has. The particle swarm optimization algorithm was used to find out the optimal order and establish the fractional order PFGM（1,1） model based on PSO. The example calculation shows that fractional order FGM（1,1） model can improve the precision of building settlement prediction. It can further improve the prediction accuracy and error inspection level by selecting the optimal order based on PSO algorithm. Thus it can be seen that the fractional order PFGM（1,1） model based on PSO plays an important guiding role in controlling the building settlement.
作者
徐云霞
王建宏
张楠
XU Yun-xia;WANG Jian-hong;ZHANG Nan(School of Civil and Architectural Engineering, Nantong University, Nantong 226019, China;School of Science, Nantong University, Nantong 226019, China)
出处
《数学的实践与认识》
北大核心
2018年第8期278-283,共6页
Mathematics in Practice and Theory
基金
江苏省大学生实践创新训练计划项目(201610304069Y)
南通市科技计划项目(MS22016051)
国家级大学生实践创新训练计划项目(201610304042Z)
